The Vehicle Routing Problem with TimeWindows (VRPTW) consists in determining the routing plan of vehicles with identical capacity in order to supply the demands of a set of customers with predefined time windows. This complex multi-constrained problem has been widely studied due to its industrial, economic and environmental implications. In this work, we are interested in defining the number of...

In practically all real-world planning and scheduling problems one is faced with uncertainty. Usually this uncertainty is abstracted away during the modeling process, such that standard combinatorial optimization algorithms can be used to solve the problem. This abstraction step is necessary, because these algorithms generally cannot deal with uncertainty. In this thesis we study the Vehicle Ro...

This paper investigates the ability of a discrete particle swarm optimization algorithm (DPSO) to evolve solutions from infeasibility to feasibility for the Vehicle Routing Problem with Time Windows (VRPTW). The proposed algorithm incorporates some principles from multi-objective optimization to allow particles to conduct a dynamic trade-off between objectives in order to reach feasibility. The...

The Pickup and Delivery Problem with Time Windows (PDPTW) is a generalization of the well studied Vehicle Routing Problem with Time Windows (VRPTW). Since it models several typical planning situations in operational transportation logistics and public transit, the PDPTW has attracted growing interest in recent years. This paper proposes a Grouping Genetic Algorithm for solving the PDPTW which f...

This paper presents an adaptive genetic algorithm (GA) to solve the Vehicle Routing Problem with Time Windows (VRPTW) to near optimal solutions. The algorithm employs a unique decoding scheme with the integer strings. It also automatically adapts the crossover probability and the mutation rate to the changing population dynamics. The adaptive control maintains population diversity at user-defin...

Efficient optimisation algorithms have become important tools for finding high-quality solutions to hard, real-world problems such as production scheduling, timetabling, or vehicle routing. These are typically “black boxes” that work on mathematical models of the problem solve. However, many difficult fully specify, and require a “human in loop” who collaborates with algorithm by refining model...

The Vehicle Routing Problem with Time Windows (VRPTW) involves servicing a set of customers, with earliest and latest time deadlines, with varying demands using capacitated vehicles with limited travel times. The objective of the problem is to service all customers while minimizing the number of vehicles and travel distance without violating the capacity and travel time of the vehicles and cust...

We study a new variant of the vehicle routing problem, called Mobile Production Vehicle Routing Problem (MoP-VRP). In this vehicles are equipped with 3D printers, and production takes place on way to customer. The objective is minimize weighted cost incurred by travel delay service. formulate Mixed Integer Programming (MIP) model develop an Adaptive Large Neighbourhood Search (ALNS) heuristic f...